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BT Technology Journal

, Volume 22, Issue 4, pp 227–240 | Cite as

Teaching Machines about Everyday Life

  • P Singh
  • B Barry
  • H Liu
Article

Abstract

In order to build software that can deeply understand people and our problems, we require computational tools that give machines the capacity to learn and reason about everyday life. We describe three commonsense knowledge bases that take unconventional approaches to representing, acquiring, and reasoning with large quantities of commonsense knowledge. Each adopts a different approach — ConceptNet is a large-scale semantic network, LifeNet is a probabilistic graphical model, and StoryNet is a database of story-scripts. We describe the evolution, architecture and operation of these three systems, and conclude with a discussion of how we might combine them into an integrated commonsense reasoning system.

Keywords

Information System Communication Network User Interface Knowledge Base Everyday Life 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • P Singh
  • B Barry
  • H Liu

There are no affiliations available

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